Título: | MOODSIC: MUSIC RECOMMENDATION APPLICATION BASED ON SENTIMENT ANALYSIS | ||||||||||||
Autor(es): |
GUILHERME DE MORAES VASSALLO |
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Colaborador(es): |
IVAN MATHIAS FILHO - Orientador |
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Catalogação: | 12/JAN/2024 | Língua(s): | PORTUGUESE - BRAZIL |
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Tipo: | TEXT | Subtipo: | SENIOR PROJECT | ||||||||||
Notas: |
[pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio. [en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio. |
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Referência(s): |
[pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/TFCs/consultas/conteudo.php?strSecao=resultado&nrSeq=65883@1 [en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/TFCs/consultas/conteudo.php?strSecao=resultado&nrSeq=65883@2 |
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DOI: | https://doi.org/10.17771/PUCRio.acad.65883 | ||||||||||||
Resumo: | |||||||||||||
This work presents the process of studying, prototyping and developing a
Web application called Moodsic, which aims to perform the sentiment analysis of
a personal report typed by the user and use the detected sentiment to search for
a playlist consistent (or opposite) to it, while also giving users the possibility of
saving those searches. The application was developed with the Django framework
and by integrating services provided by Spotify and Hugging Face via API. The
solution explores the connection between music and human sentiments, and
makes advancements in the machine-learning field explicit. The product of this
work was an application that is simple, but intuitive, functional and full of potential.
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